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I want to take this opportunity to post a new and improved version of the stacked dots template to the list. Here is a list of improvements: In addition to the stacked dots charts (line free and blue line versions), there are a number of charts that represent different ways to move from multiple daily frequencies to a reduced data set.
Each chart is designed to give you a different view of your data and allows one to see the consequences of choosing one data reduction method over another.
- acceleration and deceleration series are based on total daily frequencies taken across all timings divided by total performance time (the sum of the record floors)
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- this chart links the deceleration frequency to the highest acceleration frequency obtained for a particular day. We had referred to this chart as the Best Timing of the Day and my first run at this chart plotted best acceleration and best deceleration timings for the day. The present method seems, because of the time-lock between acceleration and deceleration series, to be more reasonable.
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- plots the highest and lowest acceleration frequency on a day line and plots the highest and lowest deceleration frequency for that same day line. This is a very good chart because it preserves total bounce while allowing the eye to follow the jumps and turns.
ratios for each day. Dashed horizontal lines break out % Correct on the right hand ordinate.
This template supports only two methods for finding the celeration line:
This is a new and improved routine based on Owen's work. The reader should review the paper Owen wrote on this method and I can make it available to the list with Owen's permission. After fairly extensive testing with large data sets I discovered that the normally proficient 'double back' criterion for finding the celeration line gets bogged down as it cycles through potentially thousands of iterations to find a solution. While the routine might ultimately return the best line, the time-cost was prohibitive. I, therefore, made a command decision to force the routine into a linear regression solution after 10 iterations. This seemed a reasonable criterion as most times the median slope method will result in a solution within 3-5 iterations. I followed this same solution when the double back criterion overtly fails. Owen proposed other solutions to this special case but they pose other programming difficulties I did not wish to tackle. If anyone is interested in how I approached the solution to Owen's method, please write me and I'll work up a summary.
This is the same routine as before but the manner in which the data are handled has been made very efficient resulting in tremendous speed gains.
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In my initial set up with the stacked dots chart, I did not pay attention placing celeration lines on the data reduction charts. In this version, no matter which chart you select (except min/max and the best-worst accuracy index charts which do not support celeration lines), the celeration finder moves the data for the specified dates and the specific data reduction method into the computational routine. This results in a unique set of celeration lines for each chart.
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This version of the template takes advantage of Excel's built in functions to vastly improve the speed for finding up, down, and total bounce.
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This version of the template uses blue up and down pointing triangles for Aimstars. If you do not see these triangles when you enter the date and frequencies, you will see an "s" or "t" on the chart instead. Click ONE TIME on the letter "s" or "t". Change the font to "Monotype Sorts." This will change the letter to the appropriate symbol. The template attached to this post should present Aimstars correctly on Windows machines, but perhaps not for Macs.
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Feel free to contact me on or off list with questions, comments, or suggestions.
Best Regards,
Stuart R. Harder
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